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Peter Flach

Peter FlachPeter Flach has more than twenty years of experience in machine learning teaching and research. He is Editor-in-Chief of Machine Learning and Program Co-Chair of the 2009 ACM Conference on Knowledge Discovery and Data Mining and the 2012 European Conerence on Machine Learning and Data Mining. His research spans all aspects of machine learning, from knowledge representation and the use of logic to learn from highly structured data to the analysis and evaluation of machine learning models and methods to large-scale data mining. He is particularly known for his innovative use of Receiver Operating Characteristic (ROC) analysis for understanding and improving machine learning methods. These innovations have proved their effectiveness in a number of invited talks and tutorials and now form the backbone of this book. Read More Read Less

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Machine Learning South Asia Edition24 %
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01 Jul 2015
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Local Applications of the Ecological Approach To Human-Machine Systems37 %
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05 Jan 1995
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Machine LearningNR
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20 Sep 2012
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The United States Marine Corps Workout27 %
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20 Feb 2004
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The Official United States Navy Seal Workout27 %
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21 Nov 2002
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Machine Learning and Knowledge Discovery in Databases36 %
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Machine Learning and Knowledge Discovery in Databases34 %
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Probleme der ausgedehnten Dünndarmresektion im Kindesalter (Kurzdarmsyndrom)21 %
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30 Jun 1975
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German
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12.
Local Applications of the Ecological Approach To Human-Machine Systems37 %
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06 Jan 1995
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Global Perspectives on the Ecology of Human-Machine Systems37 %
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05 Jan 1995
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Global Perspectives on the Ecology of Human-Machine Systems37 %
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06 Jan 1995
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15.
Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track1 % NR
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Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track, Demo Track and Industrial Track2 % NR
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Machine Learning and Knowledge Discovery in Databases. Research Track1 % NR
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Machine Learning and Knowledge Discovery in Databases. Research Track1 % NR
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Machine Learning and Knowledge Discovery in Databases. Research Track1 % NR
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Machine Learning and Knowledge Discovery in Databases. Research Track1 % NR
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